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Automated cow body condition scoring using multiple 3D cameras and convolutional neural networks
Dissertation (MEng (Computer Engineering))--University of Pretoria, 2025.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2026
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| _version_ | 1867613590227255296 |
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| access_status_str | Open Access |
| author2 | Myburgh, Hermanus Carel |
| author_browse | Myburgh, Hermanus Carel |
| author_facet | Myburgh, Hermanus Carel |
| collection | Thesis |
| dc_rights_str_mv | © 2024 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Dissertation (MEng (Computer Engineering))--University of Pretoria, 2025. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/107762 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:38:33.924Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/107762 Automated cow body condition scoring using multiple 3D cameras and convolutional neural networks Myburgh, Hermanus Carel u17012822@tuks.co.za De Freitas, Allan Summerfield, Gary Ian UCTD Sustainable Development Goals (SDGs) Automated Cow Body Condition Scoring Convolutional Neural Network Computer Vision Precision Livestock Sensor Fusion Dissertation (MEng (Computer Engineering))--University of Pretoria, 2025. Body condition scoring is an objective scoring method used to evaluate the health of a cow by determining the amount of subcutaneous fat in its body. Automated body condition scoring is becoming vital to large commercial dairy farms as it helps farmers score their cows more often and more consistently compared to manual scoring. A common approach to automated body condition scoring is to utilise a CNN-based model trained with data from a depth camera. The approach presented in this research study makes use of three depth cameras placed at different positions near the rear of a cow to train three independent CNNs. Ensemble modelling was then used to combine the estimations of the three individual CNN models. The results show that utilising the data from three depth cameras to train three separate models merged through ensemble modelling yields significantly improved automated body condition scoring accuracy compared to a single depth camera and CNN model approach. MilkSA PRJ-0312-2022 Electrical, Electronic and Computer Engineering MEng (Computer Engineering) Unrestricted Faculty of Engineering, Built Environment and Information Technology SDG-09: Industry, innovation and infrastructure 2026-02-02T08:13:01Z 2026-02-02T08:13:01Z 2026-04-01 2025-08-11 Dissertation * A2026 http://hdl.handle.net/2263/107762 https://doi.org/10.25403/UPresearchdata.23546364 en © 2024 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | UCTD Sustainable Development Goals (SDGs) Automated Cow Body Condition Scoring Convolutional Neural Network Computer Vision Precision Livestock Sensor Fusion Automated cow body condition scoring using multiple 3D cameras and convolutional neural networks |
| title | Automated cow body condition scoring using multiple 3D cameras and convolutional neural networks |
| title_full | Automated cow body condition scoring using multiple 3D cameras and convolutional neural networks |
| title_fullStr | Automated cow body condition scoring using multiple 3D cameras and convolutional neural networks |
| title_full_unstemmed | Automated cow body condition scoring using multiple 3D cameras and convolutional neural networks |
| title_short | Automated cow body condition scoring using multiple 3D cameras and convolutional neural networks |
| title_sort | automated cow body condition scoring using multiple 3d cameras and convolutional neural networks |
| topic | UCTD Sustainable Development Goals (SDGs) Automated Cow Body Condition Scoring Convolutional Neural Network Computer Vision Precision Livestock Sensor Fusion |
| url | http://hdl.handle.net/2263/107762 https://doi.org/10.25403/UPresearchdata.23546364 |